# pylint: skip-file
# pylint: disable=line-too-long
"""Create quantized model from JSON files..."""
import os
import warnings
import mxnet as mx
from mxnet.context import cpu
from mxnet.gluon import SymbolBlock
from gluoncv.utils.compress_json import get_compressed_model

__all__ = ['mobilenet1_0_int8', 'resnet50_v1_int8',
           'ssd_300_vgg16_atrous_voc_int8', 'ssd_512_mobilenet1_0_voc_int8',
           'ssd_512_resnet50_v1_voc_int8', 'ssd_512_vgg16_atrous_voc_int8',
           'fcn_resnet101_voc_int8', 'fcn_resnet101_coco_int8']

_compressed_int8_json = {
    'fcn_resnet101_voc_int8': b'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',
    'fcn_resnet101_coco_int8': 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'
}

def _not_impl(*args, **kwargs):
    raise NotImplementedError("Not yet implemented for quantized models")

def _create_quantized_models(name, sym_prefix):
    def func(pretrained=False, tag=None, root='~/.mxnet/models', ctx=cpu(0), **kwargs):
        r"""Quantized model.

        Parameters
        ----------
        pretrained : bool or str
            Boolean value controls whether to load the default pretrained weights for model.
            String value represents the hashtag for a certain version of pretrained weights.
        tag : str, default is None
            Optional length-8 sha1sum of parameter file. If `None`, best parameter file
            will be used.
        ctx : Context, default CPU
            The context in which to load the pretrained weights.
        root : str, default $MXNET_HOME/models
            Location for keeping the model parameters.
        """
        from ..model_zoo import get_model
        from ..model_store import get_model_file
        curr_dir = os.path.abspath(os.path.dirname(__file__))
        model_name = name.replace('mobilenet1_', 'mobilenet1.')
        model_name = model_name.replace('mobilenet0_', 'mobilenet0.')
        with warnings.catch_warnings(record=True) as w:
            warnings.simplefilter("always")
            import tempfile
            if "fcn" in model_name:
                model_json = get_compressed_model(model_name, _compressed_int8_json)
                fd, path = tempfile.mkstemp(dir=curr_dir, suffix='.json', text=True)
                with open(path, 'w') as f:
                    f.write(model_json)
                sym_net = SymbolBlock.imports(path, ['data'], None, ctx=ctx)
                os.close(fd)
                try:
                    os.remove(path)
                except:
                    pass
            else:
                json_file = os.path.join(curr_dir, '{}-symbol.json'.format(model_name))
                sym_net = SymbolBlock.imports(json_file, ['data'], None, ctx=ctx)
            base_name = '_'.join(model_name.split('_')[:-1])
            param_file = get_model_file(base_name, tag=tag, root=root) if pretrained else None
            net = get_model('_'.join(model_name.split('_')[:-1]), prefix=sym_prefix)
            classes = getattr(net, 'classes', [])
            if param_file:
                # directly imports weights saved by save_parameters is not applicable
                # so we hack it by load and export once to a temporary params file
                net.load_params(param_file)
                net.hybridize()
                if '512' in base_name:
                    net(mx.nd.zeros((1, 3, 512, 512)))
                elif '300' in base_name:
                    net(mx.nd.zeros((1, 3, 300, 300)))
                else:
                    net(mx.nd.zeros((1, 3, 224, 224)))
                with tempfile.TemporaryDirectory() as tmpdirname:
                    prefix = os.path.join(tmpdirname, 'tmp')
                    net.export(prefix, epoch=0)
                    param_prefix = prefix + '-0000.params'
                    sym_net.collect_params().load(param_prefix)
        sym_net.classes = classes
        sym_net.reset_class = _not_impl
        sym_net.set_nms = _not_impl
        return sym_net
    func.__name__ = name
    globals()[name] = func

_create_quantized_models('mobilenet1_0_int8', 'mobilenet0_')
_create_quantized_models('resnet50_v1_int8', 'resnetv10_')
_create_quantized_models('ssd_300_vgg16_atrous_voc_int8', 'ssd0_')
_create_quantized_models('ssd_512_mobilenet1_0_voc_int8', 'ssd0_')
_create_quantized_models('ssd_512_resnet50_v1_voc_int8', 'ssd0_')
_create_quantized_models('ssd_512_vgg16_atrous_voc_int8', 'ssd0_')
_create_quantized_models('fcn_resnet101_voc_int8', 'fcn0_')
_create_quantized_models('fcn_resnet101_coco_int8', 'fcn0_')
